Deep focus approach for accurate bone age estimation from lateral cephalogram.

Background/purpose: Bone age is a useful indicator of children's growth and development. Recently, the rapid development of deep-learning technique has shown promising results in estimating bone age. This study aimed to devise a deep-learning approach for accurate bone-age estimation by focusing on the cervical vertebrae on lateral cephalograms of growing children using image segmentation. Materials and methods: We included 900 participants, aged 4-18 years, who underwent lateral cephalogram and hand-wrist radiograph on the same day. First, cervical vertebrae segmentation was performed from the lateral cephalogram using DeepLabv3+ architecture. Second, after extracting the region of interest from the segmented image for preprocessing, bone age was estimated through transfer learning using a regression model based on Inception-ResNet-v2 architecture. The dataset was divided into train:test sets in a ratio of 4:1; five-fold cross-validation was performed at each step. Results: The segmentation model possessed average accuracy, intersection over union, and mean boundary F1 scores of 0.956, 0.913, and 0.895, respectively, for the segmentation of cervical vertebrae from lateral cephalogram. The regression model for estimating bone age from segmented cervical vertebrae images yielded average mean absolute error and root mean squared error values of 0.300 and 0.390 years, respectively. The coefficient of determination of the proposed method for the actual and estimated bone age was 0.983. Our method visualized important regions on cervical vertebral images to make a prediction using the gradient-weighted regression activation map technique. Conclusion: Results showed that our proposed method can estimate bone age by lateral cephalogram with sufficiently high accuracy.

Upregulation of thromboxane synthase mediates visfatin-induced interleukin-8 expression and angiogenic activity in endothelial cells.

Thromboxane synthase (TXAS) is an enzyme that catalyzes the synthesis of thromboxane A(2) (TXA(2)). Overexpression of TXAS is associated with a variety of vascular diseases. Recently, we reported that visfatin, a novel adipokine, exhibits angiogenic actions. In this study, we showed that visfatin increased mRNA and protein levels of TXAS and stimulated TXA(2) biosynthesis in vascular endothelial cells. In addition, visfatin induced the expression and secretion of interleukin-8 (IL-8), which is blocked by a TXAS inhibitor and by the transfection of siRNA specific for TXAS. Furthermore, the inhibition of TXAS activity and blockade of the IL-8 receptor attenuated visfatin-induced endothelial angiogenesis. Together, these results showed that visfatin promoted IL-8 production by upregulation of TXAS, leading to angiogenic activation in endothelial cells.

Evaluation of intersegmental displacement according to osteosynthesis method for mandibular setback sagittal split ramus osteotomy using cone-beam computed tomographic superimposition.

PURPOSE: To compare intersegmental displacements after mandibular setback sagittal split ramus osteotomy with reference to the fixation system applied: miniplate with monocortical screw, 3 bicortical screws, and 1 bicortical screw and 2 resorbable screws. MATERIALS AND METHODS: The 42 subjects were divided into 3 groups according to the osteosynthesis method applied. To evaluate the intersegmental displacements from immediately after surgery (T0) to 6 months after surgery (T1), 2 cone-beam computed tomographic data sets were superimposed on the symphyseal area and the lower part of the mandible below the root apex. On the superimposed 3-dimensional images, the mean and standard deviation of the differences of the coordinates (x, y, z) between T0 and T1 were calculated. RESULTS: From T0 to T1, group B (bicortical screws) manifested the greatest condylion (Cd) and coronoid process (Cp) displacements (P < .05). In group A, the right Cd moved anteriorly and the left Cd moved anteriorly and inferiorly, whereas the right and left Cps moved anteriorly. In group B, the right and left Cps moved laterally and inferiorly. In group C, the right Cd moved anteriorly and inferiorly, the left Cd changed laterally and anteriorly, the right Cp moved anteriorly, and the left Cp moved anteriorly and inferiorly. CONCLUSIONS: In the present study, group B (bicortical screws) showed the greatest displacement after the healing period. In view of these findings, surgeons should consider carefully their choice of osteosynthesis method to effectively decrease intersegmental displacement.

Effect of bimaxillary surgery on adaptive condylar head remodeling: metric analysis and image interpretation using cone-beam computed tomography volume superimposition.

PURPOSE: The aim of the present study was to use cone-beam computed tomography volume superimposition to investigate the effect of bimaxillary orthognathic surgery on condylar head remodeling. MATERIALS AND METHODS: Using a retrospective study design, 2 investigators evaluated the cone-beam computed tomography data of subjects who had undergone Le Fort I osteotomy and mandibular setback surgery. The predictor variable was time, grouped as preoperative versus postoperative. The outcome variables were the measurement changes of the condylar heads and the distribution of the condylar head remodeling signs. Paired t and χ(2) tests were performed for the purposes of the 2-dimensional metric analysis and the condylar head remodeling distribution. P < .05 was considered significant. RESULTS: The sample was composed of 22 adults (11 men and 11 women, age 20.3 ± 3.2 years) diagnosed with skeletal Class III malocclusion. The intra- and interoperator reliabilities of the image interpretation showed substantial agreement, according to Cohen's kappa index. The condylar heights on the sagittal and coronal planes decreased after surgery. Bone resorption occurred predominantly in the anterior and superior areas on the sagittal plane, the superior and lateral areas on the coronal plane, and the anterolateral and posterolateral areas on the axial plane (P < .05). Bone formation was apparent only in the anteromedial area on the axial plane (P < .05). CONCLUSIONS: Bimaxillary orthognathic surgery caused a decrease in the condylar heights and condylar head remodeling. The cone-beam computed tomography volume superimposition method showed that the condylar head had undergone remodeling after bimaxillary surgery.

Aggressive central odontogenic fibroma in the maxilla: A case report.

A central odontogenic fibroma is a rare benign tumor composed of mature fibrous connective tissue with variable amounts of odontogenic epithelium. It appears at similar rates in the maxilla and mandible. In the maxilla, it usually occurs anterior to the molars. Radiographically, central odontogenic fibroma commonly presents as a multilocular or unilocular radiolucency with a distinct border. This paper reports a case of an aggressive central odontogenic fibroma involving the right posterior maxilla of a 53-year-old man. Radiographs showed an extensive soft tissue mass involving the entire right maxilla with frank bone resorption. The patient had a history of 2 operations in the region, both more than 2 decades ago. Although it was impossible to confirm the previous diagnoses, it was presumed that this case was a recurrent lesion.

Analysis of the root position and angulation of maxillary premolars in alveolar bone using cone-beam computed tomography.

Purpose: This study investigated whether the relationship between the maxillary sinus and the root of the maxillary premolar is correlated with the root position and whether there is a difference in the long axis angle of premolars and the buccal bone thickness according to the sinus-root relationship and root position. Materials and Methods: Cone-beam computed tomographic images of 587 maxillary first premolars and 580 second premolars from 303 patients were retrospectively reviewed. The maxillary sinus floor-root relationship was classified into 4 types, and the root position in the alveolar bone was evaluated as buccal, middle, or palatal. The long axis angle of the maxillary premolars in the alveolar bone and the buccal bone thickness were measured. The correlation between these parameters was analyzed. Results: The maxillary sinus floor-root relationship showed a statistically significant correlation with the root position in the alveolar bone. Most maxillary first premolars were buccally located, and more than half of the second premolars had their roots in the middle. The long axis angle of the premolars was significantly larger in buccal-positioned teeth than in middle-positioned teeth, and the buccal bone was thinner. Conclusion: When the root of the maxillary premolar was separated from the sinus floor, the premolar was often located on the buccal side. Most of the maxillary first premolars had a thinner buccal bone and larger inclination than the second premolars. It is recommended to evaluate the root position, sagittal angle and buccal bone thickness using CBCT for implant treatment planning.

Automated Mesiodens Classification System Using Deep Learning on Panoramic Radiographs of Children.

In this study, we aimed to develop and evaluate the performance of deep-learning models that automatically classify mesiodens in primary or mixed dentition panoramic radiographs. Panoramic radiographs of 550 patients with mesiodens and 550 patients without mesiodens were used. Primary or mixed dentition patients were included. SqueezeNet, ResNet-18, ResNet-101, and Inception-ResNet-V2 were each used to create deep-learning models. The accuracy, precision, recall, and F1 score of ResNet-101 and Inception-ResNet-V2 were higher than 90%. SqueezeNet exhibited relatively inferior results. In addition, we attempted to visualize the models using a class activation map. In images with mesiodens, the deep-learning models focused on the actual locations of the mesiodens in many cases. Deep-learning technologies may help clinicians with insufficient clinical experience in more accurate and faster diagnosis.

Tomographic similarity scan with a computed modified absolute mandibular midsagittal plane for precise and objective localization of mandibular asymmetry.

The application of 3D imaging is at its cusp in craniofacial diagnosis and treatment planning. However, most applications are limited to simple subjective superimposition-based analysis. As the diagnostic accuracy dictates the precision in operability, we propose a novel method that enables objective clinical decision making for patients with mandibular asymmetry. We analyzed cone-beam computed tomography (CBCT) scans of 34 patients who underwent surgical correction for mandibular asymmetry using a high-throughput computing algorithm. Radiomic segmentation of quantitative features of surface and volume followed by exploration resulted in identification of a computed modified absolute mandibular midsagittal plane (cmAMP). Tomographic similarity scan (ToSS) curves were generated via bilateral equidistant scanning in an antero-posterior direction with cmAMP as the reference. ToSS comprised of a comprehensive similarity index (SI) score curve and a segment-wise volume curve. The SI score was computed using the Sørensen-Dice similarity coefficient ranging from 0 to 1. The volumetric analysis was represented as the non-overlapping volume (NOV) and overlapping volume (OV) for each segment, with two segmentation lines, at the mental foramen anteriorly and the intraoral vertical ramus osteotomy region posteriorly. Statistical analysis showed strong negative correlation between the NOV and SI scores for the anterior, middle, and total mandible (P < 0.001). Additionally, a significant correlation was observed between the change in the SI scores for anterior (P = 0.044) and middle segments (P < 0.001) to the total mandible when comparing the data before and after the surgery. This work demonstrated the potential of incorporating ToSS curves in surgical simulation software to improve precision in the clinical decision-making process.

Effect of diode-pumped solid state laser on polymerization shrinkage and color change in composite resins.

A diode-pumped solid state (DPSS) laser emitting at 473 nm was used to test its influence on the degree of polymerization of composite resins. Eight composite resins were chosen and light cured with three different light-curing systems [a quartz-tungsten-halogen (QTH) lamp-based unit, a light-emitting diode (LED) unit, and a DPSS laser]. Polymerization shrinkage and color change in specimens were measured. According to the statistical analysis, each light-curing system produced a significantly different value of maximum polymerization shrinkage. In most specimens, the DPSS laser induced the least polymerization shrinkage. After being immersed in distilled water for 10 days, specimens light-cured by the DPSS laser had undergone less color change than those cured by the other units. In conclusion, the DPSS laser induced better or similar polymerization in terms of polymerization shrinkage and color change in composite resins compared with those of the QTH lamp-based and LED units.

Comparison of panoramic radiography and cone-beam computed tomography for assessing radiographic signs indicating root protrusion into the maxillary sinus.

PURPOSE: This study investigated correlations between findings on panoramic radiographs and cone-beam computed tomography (CBCT) to assess the relationship between the maxillary sinus floor and the roots of maxillary posterior teeth. In addition, radiographic signs indicating actual root protrusion into the maxillary sinus were evaluated on panoramic radiographs. MATERIALS AND METHODS: Paired panoramic radiographs and CBCT images from 305 subjects were analyzed. This analysis classified 2,440 maxillary premolars and molars according to their relationship with the maxillary sinus floor on panoramic radiographs and CBCT images. In addition, interruption of the sinus floor was examined on panoramic radiographs. RESULTS: Root protrusion into the maxillary sinus occurred most frequently in the mesiobuccal roots of the second molars. The classification according to panoramic radiographs and CBCT images was the same in more than 90% of cases when there was no contact between the root apex and the sinus floor. When the panoramic radiograph showed root protrusion into the sinus, the CBCT images showed the same classification in 67.5% of second molars, 48.8% of first molars, and 53.3% of second premolars. There was a statistically significant relationship between interruption of the sinus floor on panoramic radiographs and root protrusion into the sinus on CBCT images. CONCLUSION: The presence of root protrusion into the sinus on panoramic radiographs demonstrated a moderate ability to predict root protrusion into the maxillary sinus. Interruption of the maxillary sinus floor could be considered an indicator of actual root protrusion into the maxillary sinus.

Ameloblastic carcinoma of the mandible: A case report.

Ameloblastic carcinoma is a rare odontogenic malignant tumor with the histologic features of both ameloblastoma and carcinoma. It occurs more frequently in the mandible than in the maxilla and it may appear de novo or develop from a preexisting ameloblastoma or odontogenic cyst. Rapidly progressing, painful swelling is the most common symptom, and radiographically, it shows significant bone resorption and cortical perforation. This report described a case of ameloblastic carcinoma in a 45-year-old man who presented with swelling in the left mandible. The lesion showed combined features of benign findings, such as an expansile cortex with a distinct border, and malignant findings, such as a large exophytic mass with frank bone resorption. Excisional biopsy was performed and a final diagnosis of ameloblastic carcinoma was made.

Very deep super-resolution for efficient cone-beam computed tomographic image restoration.

PURPOSE: As cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images. MATERIALS AND METHODS: Virtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images. RESULTS: The images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1. CONCLUSION: VDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

In the absence of accurate medical records, it is critical to correctly classify implant fixture systems using periapical radiographs to provide accurate diagnoses and treatments to patients or to respond to complications. The purpose of this study was to evaluate whether deep neural networks can identify four different types of implants on intraoral radiographs. In this study, images of 801 patients who underwent periapical radiographs between 2005 and 2019 at Yonsei University Dental Hospital were used. Images containing the following four types of implants were selected: Brånemark Mk TiUnite, Dentium Implantium, Straumann Bone Level, and Straumann Tissue Level. SqueezeNet, GoogLeNet, ResNet-18, MobileNet-v2, and ResNet-50 were tested to determine the optimal pre-trained network architecture. The accuracy, precision, recall, and F1 score were calculated for each network using a confusion matrix. All five models showed a test accuracy exceeding 90%. SqueezeNet and MobileNet-v2, which are small networks with less than four million parameters, showed an accuracy of approximately 96% and 97%, respectively. The results of this study confirmed that convolutional neural networks can classify the four implant fixtures with high accuracy even with a relatively small network and a small number of images. This may solve the inconveniences associated with unnecessary treatments and medical expenses caused by lack of knowledge about the exact type of implant.

Automatic mandibular canal detection using a deep convolutional neural network.

The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques for automatic prediction and detection are being widely researched. Particularly in dentistry, for various reasons, automated mandibular canal detection has become highly desirable. The positioning of the inferior alveolar nerve (IAN), which is one of the major structures in the mandible, is crucial to prevent nerve injury during surgical procedures. However, automatic segmentation using Cone beam computed tomography (CBCT) poses certain difficulties, such as the complex appearance of the human skull, limited number of datasets, unclear edges, and noisy images. Using work-in-progress automation software, experiments were conducted with models based on 2D SegNet, 2D and 3D U-Nets as preliminary research for a dental segmentation automation tool. The 2D U-Net with adjacent images demonstrates higher global accuracy of 0.82 than naïve U-Net variants. The 2D SegNet showed the second highest global accuracy of 0.96, and the 3D U-Net showed the best global accuracy of 0.99. The automated canal detection system through deep learning will contribute significantly to efficient treatment planning and to reducing patients' discomfort by a dentist. This study will be a preliminary report and an opportunity to explore the application of deep learning to other dental fields.

Maxillary antroliths detected by cone-beam computed tomography in an adult dental population.

PURPOSE: This study evaluated the prevalence and characteristics of maxillary antroliths using cone-beam computed tomography (CBCT) scans performed for maxillofacial diagnostic purposes. MATERIALS AND METHODS: CBCT scans of 13,946 patients over the age of 20 were reviewed for maxillary antroliths, and prevalence according to sex, age, and the side of the jaw was calculated. The relationships of single or multiple antroliths with sex, side, and the degree of sinus inflammation were evaluated. The shape and dimension of antroliths were also assessed. The data were analyzed using descriptive statistics, the chi-square or Fisher exact tests, and Kendall's tau-b. RESULTS: A total of 138 (0.99%) of the 13,946 patients showed an antrolith in at least 1 sinus. Only 18 patients presented a bilateral manifestation, which brought the total number of sinuses containing an antrolith to 156 (0.56%). Multiple antroliths were observed in 36 sinuses, and the total number of antroliths was 207: 110 punctate, 65 linear, and 32 amorphous. The antrolith dimensions varied from 1 mm2 to 91 mm2 (average, 10.2±15.5 mm2). No statistically significant differences were found according to sex, side, and age group (P>0.05). However, there was a statistically significant difference between the multiplicity of antrolith and the degree of sinus inflammation (P<0.05). CONCLUSION: Cone-beam computed tomography is an effective modality for the detection of incidental antroliths. Maxillary antroliths were found to be very rare and were usually asymptomatic. Dentists should have a comprehensive understanding of their diagnosis and treatment in light of possible associated dental problems.

An overview of deep learning in the field of dentistry.

PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about deep learning that were applied to the field of oral and maxillofacial radiology. MATERIALS AND METHODS: A systematic review was performed using Pubmed, Scopus, and IEEE explore databases to identify articles using deep learning in English literature. The variables from 25 articles included network architecture, number of training data, evaluation result, pros and cons, study object and imaging modality. RESULTS: Convolutional Neural network (CNN) was used as a main network component. The number of published paper and training datasets tended to increase, dealing with various field of dentistry. CONCLUSION: Dental public datasets need to be constructed and data standardization is necessary for clinical application of deep learning in dental field.

Langerhans cell histiocytosis of the mandible: two case reports and literature review.

Langerhans cell histiocytosis (LCH) is a rare disorder characterized by the proliferation of dendritic cells resulting in local or systemic symptoms. The clinical symptoms of patients with Langerhans cell histiocytosis depend on the site and the degree of involvement. This article describes two case histories of unifocal bony Langerhans cell histiocytosis with mandibular involvement and further discusses the appropriate management of such via a review of the literature.

Similarity index for intuitive assessment of three-dimensional facial asymmetry.

Evaluation of facial asymmetry generally involves landmark-based analyses that cannot intuitively assess differences in three-dimensional (3D) stereoscopic structures between deviation and non-deviation sides. This study tested a newly developed similarity index that uses a mirroring technique to intuitively evaluate 3D mandibular asymmetry, and characterised the resulting lower facial soft tissue asymmetry. The similarity index was used to evaluate asymmetry before and after surgery in 46 adult patients (27 men, 19 women; age, 22 ± 4.8 years) with skeletal Class III malocclusion and facial asymmetry who underwent conventional bimaxillary orthognathic surgery. Relative to the midsagittal plane used as the reference plane, the non-overlapping volume of the mandible significantly decreased, and the similarity index significantly increased after surgery. Similarity indexes of the mandible and lower facial soft tissue were strongly negatively correlated with non-overlapping volumes of each measurement. Differences in bilateral hemi-mandibular and hemi-lower facial soft tissue surface and volume measurements before surgery were significantly negatively correlated with similarity indexes of the mandible before and after surgery. This newly developed similarity index and non-overlapping volume using a mirroring technique can easily and intuitively evaluate overall 3D morphological discrepancies, especially 3D mandibular asymmetry, before and after surgery in skeletal Class III patients with facial asymmetry.

Location and shape of the mandibular lingula: Comparison of skeletal class I and class III patients using panoramic radiography and cone-beam computed tomography.

PURPOSE: The aim of this study was to compare the location and the shape of the mandibular lingula in skeletal class I and III patients using panoramic radiography and cone-beam computed tomography. MATERIALS AND METHODS: The sample group included 190 skeletal class I patients and 157 class III patients. The location of the lingula in relation to the deepest point of the coronoid notch was classified into 3 types using panoramic radiographs. The shapes of the lingulae were classified into nodular, triangular, truncated, or assimilated types using cone-beam computed tomographic images. The data were analyzed using the chi-square test. RESULTS: The tips of the lingulae were at the same level as the coronoid notch in 75.3% of skeletal class I patients and above the coronoid notch in 66.6% of class III patients. The positions of the lingulae in relation to the deepest point of the coronoid notch showed statistically significant differences between class I and class III patients. The most common shape was nodular, and the least common was the assimilated shape. Although this trend was not statistically significant, the triangular shape was more frequently observed in class III patients than in class I patients. CONCLUSION: The locations and the shapes of the mandibular lingulae were variable. Most of the lingulae were at the same level as the coronoid notch in skeletal class I patients and above the coronoid notch in skeletal class III patients. The nodular and assimilated-shaped lingulae were the most and the least prevalent, respectively.

Automatic analysis algorithm for acquiring standard dental and mandibular shape data using cone-beam computed tomography.

This study aims to introduce a new algorithm developed using retrospective cone-beam computed tomography (CBCT) data to obtain a standard dental and mandibular arch shape automatically for an optimal panoramic focal trough. A custom-made program was developed to analyze each arch shape of randomly collected 30 CBCT images. First, volumetric data of the mandible were binarized and projected in the axial direction to obtain 2-dimensional arch images. Second, 30 patients' mandibular arches were superimposed on the center of the bilateral distal contact points of the mandibular canines to generate an average arch shape. Third, the center and boundary of a panoramic focal trough were obtained using smoothing splines. As a result, the minimum thickness and transition of the focal trough could be obtained. If this new algorithm is applied to big data of retrospective CBCT images, standard focal troughs could be established by race, sex, and age group, which would improve the image quality of dental panoramic radiography.